Bio：

Chong-Yung Chi (S’83-M’83-SM’89) received the Ph.D. degree in Electrical Engineering from the University of Southern California in 1983. From 1983 to 1988, he was with the Jet Propulsion Laboratory, Pasadena, California.

He has been a Professor with the Department of Electrical Engineering since 1989 and the Institute of Communications Engineering (ICE) since 1999 (also the Chairman of ICE for 2002-2005), National Tsing Hua University, Hsinchu, Taiwan. He co-authored a technical book, Blind Equalization and System Identification, published by Springer 2006, and published more than 150 technical (journal and conference) papers. His current research interests include signal processing for wireless communications, convex analysis and optimization for blind source separation, biomedical imaging and hyperspectral imaging.

Dr. Chi is a senior member of IEEE. He has been a Technical Program Committee member for many IEEE sponsored and co-sponsored workshops, symposiums and conferences on signal processing and wireless communications, including Co-organizer and general Co-chairman of IEEE SPAWC 2001, and Co-Chair of Signal Processing for Communications Symposium, ChinaCOM 2008 & ChinaCOM 2009. He was an Associate Editor of IEEE Trans. Signal Processing (5/2001-4/2006), IEEE Trans. Circuits and Systems II (1/2006-12/2007), and a member of Editorial Board of EURASIP Signal Processing Journal (6/2005-5/2008), and an editor (7/2003-12/2005) as well as a Guest Editor (2006) of EURASIP Journal on Applied Signal Processing. Currently, he is an Associate Editor of IEEE Signal Processing Letters and IEEE Trans. Circuits and Systems I, and a member of IEEE Signal Processing Committee on Signal Processing Theory and Methods.

Abstract:

This talk presents a training-based channel estimation scheme for achieving quality-of-service discrimination between legitimate and unauthorized receivers in wireless multiple-input multiple-output (MIMO) channels. This scheme has applications ranging from user discrimination in wireless TV broadcast systems to the prevention of eavesdropping in secret communications. By considering a wireless MIMO system that consists of a multiple-antenna transmitter, a legitimate receiver (LR) and an unauthorized receiver (UR), we present a multi-stage training-based discriminatory channel estimation (DCE) scheme that aims to optimize the channel estimation performance of the LR while limiting the channel estimation performance of the UR. The key idea is to exploit the channel estimate fed back from the LR at the beginning of each stage to enable the judicious use of artificial noise (AN) in the training signal. Specifically, with knowledge of the LR’s channel, AN can be properly superimposed with the training data to degrade the UR’s channel without causing strong interference on the LR. The channel estimation performance of the LR in earlier stages may not be satisfactory due to the inaccuracy of the channel estimate and constraints on the UR’s estimation performance, but can improve rapidly in later stages as the quality of channel estimate improves. The training data power and AN power are optimally allocated by minimizing the normalized mean squared error (NMSE) of the LR subject to a lower limit constraint on the NMSE of the UR. The presented DCE scheme is then extended to the case with multiple LRs and multiple URs. Simulation results are presented to demonstrate the effectiveness of the proposed DCE scheme.